Diagnostic analysis of liver B ultrasonic texture features based on LM neural network-Reference-Cited by-同舟云学术

Diagnostic analysis of liver B ultrasonic texture features based on LM neural network

Published:2017 Issue: Volume: Page:
ISSN:0094-243X
Container-title:AIP Conference Proceedings
language:
Short-container-title:

Author:

Chi Qingyun,Hua Hu,Liu Menglin,Jiang Xiuying

Publisher

Author(s)

Link

http://aip.scitation.org/doi/pdf/10.1063/1.4977326

Reference11 articles.

1. Ji Jianfeng, Zhou Wei, Guo Jia et al. Ultrasonic Electrograph in Differentiating Benign and Malignant Liver Tumors [J]. Chinese Journal of Ultrasound in Medicine, 2011, 27(3): 243–245.

2. Lin Senhao, Dinghong. Advances of Ultrasound Electrograph to Assess Liver Fibrosis [J]. Chinese Journal of Hepatobiliary Surgery, 2012, 18(2): 158–160.

3. Jiao Pengpeng, Guo Yizheng, Liu Lijuan et al. Matlab Implementation of Texture Feature Extraction of Grey Level Co-occurrence Matrix [J]. Computer Technology and Development, 2012, 22(11): 169–175.

4. Textural Features for Image Classification

5. Huang Jing. Research on Image Classification Based on Fractal Dimension and Grey Level Co-occurrence Matrix [D]. Master’s Thesis of Wuhan University of Technology, 2008.

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Liver Pathological States Identification with Self-organization Models Based on Ultrasound Images Texture Features;Advances in Intelligent Systems and Computing;2020-12-23

2. Liver Pathological States Identification in Diffuse Diseases with Self-Organization Models Based on Ultrasound Images Texture Features;2020 IEEE 15th International Conference on Computer Sciences and Information Technologies (CSIT);2020-09-23